Automatic Detection of Inauthentic Templated Responses in English Language Assessments

In high-stakes English Language Assessments, low-skill test takers may employ memorized materials called templates'' on essay questions to game’’ or fool the automated scoring system. In this study, we introduce the automated detection of inauthentic, templated responses (AuDITR) task, describe a machine learning-based approach to this task and illustrate the importance of regularly updating these models in production.